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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<conference: string, category: string, sheet: string, accepted_tags: string, authors_included: bool, year: int64, cutoff_period: string, track: string, conference_group: string, source_split: string, source_dataset: string>
to
{'conference': Value('string'), 'category': Value('string'), 'sheet': Value('string'), 'accepted_tags': Value('string'), 'authors_included': Value('bool'), 'year': Value('int64'), 'cutoff_period': Value('string'), 'source_csv': Value('string'), 'url': Value('string'), 'pdf_url': Value('string'), 'track': Value('string'), 'conference_group': Value('string'), 'tags': Value('string')}
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2224, in cast_table_to_schema
                  cast_array_to_feature(
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2092, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<conference: string, category: string, sheet: string, accepted_tags: string, authors_included: bool, year: int64, cutoff_period: string, track: string, conference_group: string, source_split: string, source_dataset: string>
              to
              {'conference': Value('string'), 'category': Value('string'), 'sheet': Value('string'), 'accepted_tags': Value('string'), 'authors_included': Value('bool'), 'year': Value('int64'), 'cutoff_period': Value('string'), 'source_csv': Value('string'), 'url': Value('string'), 'pdf_url': Value('string'), 'track': Value('string'), 'conference_group': Value('string'), 'tags': Value('string')}
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1339, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 972, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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{ "conference": "ACL 2025", "category": "Best paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1454", "pdf_url": "", "track": null, "confe...
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{ "conference": "ACL 2025", "category": "Best paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1126", "pdf_url": "", "track": null, "confer...
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{ "conference": "ACL 2025", "category": "Best Social Impact Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.96", "pdf_url": "", "track": nu...
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{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.71", "pdf_url": "", "track": null, "...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
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{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.115", "pdf_url": "", "track": null, "...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
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{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1319", "pdf_url": "", "track": null, ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: IndicSynth: A Large-Scale Multilingual Synthetic Speech Dataset for Low-Resource Indian Languages Abstract: Recent advances in synthetic speech generation technology have facilitated the generation of high-quality synthetic (fake) speech that emulates human voices. These technologies pose a threat of misuse for ...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1070", "pdf_url": "", "track": null, ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: LaTIM: Measuring Latent Token-to-Token Interactions in Mamba Models Abstract: State space models (SSMs), such as Mamba, have emerged as an efficient alternative to transformers for long-context sequence modeling. However, despite their growing adoption, SSMs lack the interpretability tools that have been crucial...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1194", "pdf_url": "", "track": null, ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Llama See, Llama Do: A Mechanistic Perspective on Contextual Entrainment and Distraction in LLMs Abstract: We observe a novel phenomenon, *contextual entrainment*, across a wide range of language models (LMs) and prompt settings, providing a new mechanistic perspective on how LMs become distracted by “irrelevant...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.791", "pdf_url": "", "track": null, "...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts Abstract: Safety concerns in large language models (LLMs) have gained significant attention due to their exposure to potentially harmful data during pre-training. In this paper, we identify a new safety vulnerability in LLMs...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1207", "pdf_url": "", "track": null, ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Mapping 1,000+ Language Models via the Log-Likelihood Vector Abstract: To compare autoregressive language models at scale, we propose using log-likelihood vectors computed on a predefined text set as model features. This approach has a solid theoretical basis: when treated as model coordinates, their squared Euc...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1584", "pdf_url": "", "track": null, ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models Abstract: Long Context Understanding (LCU) is a critical area for exploration in current large language models (LLMs). However, due to the inherently lengthy nature of long-text data, existing LCU benchmarks for LLMs often...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.560", "pdf_url": "", "track": null, ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: PARME: Parallel Corpora for Low-Resourced Middle Eastern Languages Abstract: The Middle East is characterized by remarkable linguistic diversity, with over 400 million inhabitants speaking more than 60 languages across multiple language families. This study presents a pioneering work in developing the first para...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1451", "pdf_url": "", "track": null, ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Past Meets Present: Creating Historical Analogy with Large Language Models Abstract: Historical analogies, which compare known past events with contemporary but unfamiliar events, are important abilities that help people make decisions and understand the world. However, research in applied history suggests that ...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.200", "pdf_url": "", "track": null, "...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Pre³: Enabling Deterministic Pushdown Automata for Faster Structured LLM Generation Abstract: Extensive LLM applications demand efficient structured generations, particularly for LR(1) grammars, to produce outputs in specified formats (e.g., JSON). Existing methods primarily parse LR(1) grammars into a pushdown ...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.551", "pdf_url": "", "track": null, ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory Abstract: Recently, scaling test-time compute on Large Language Models (LLM) has garnered wide attention. However, there has been limited investigation of how various reasoning prompting strategies perform a...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1356", "pdf_url": "", "track": null, ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability Abstract: In generative commonsense reasoning tasks such as CommonGen, generative large language models (LLMs) compose sentences that include all given concepts. However, when focusing on instruc...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1508", "pdf_url": "", "track": null, ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Toward Automatic Discovery of a Canine Phonetic Alphabet Abstract: Dogs communicate intelligently but little is known about the phonetic properties of their vocalization communication. For the first time, this paper presents an iterative algorithm inspired by human phonetic discovery, which is based on minimal p...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.451", "pdf_url": "", "track": null, "...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Towards the Law of Capacity Gap in Distilling Language Models Abstract: Language model (LM) distillation aims at distilling the knowledge in a large teacher LM to a small student one. As a critical issue facing LM distillation, a superior student often arises from a teacher of a relatively small scale instead of...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1097", "pdf_url": "", "track": null, ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling Abstract: The rapid growth in the parameters of LLMs has made inference latency a fundamental bottleneck. Speculative decoding represents a lossless approach to accelerate inference through a guess-and-verify paradi...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.338", "pdf_url": "", "track": null, ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Typology-Guided Adaptation in Multilingual Models Abstract: Multilingual models often treat language diversity as a problem of data imbalance, overlooking structural variation. We introduce the *Morphological Index* (MoI), a typologically grounded metric that quantifies how strongly a language relies on surface ...
{ "conference": "ACL 2025", "category": "Outstanding Paper", "sheet": "ACL", "accepted_tags": "ACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1059", "pdf_url": "", "track": null, ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Best
Title: The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models Abstract: As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently assess LMs using...
{ "conference": "NAACL 2025", "category": "Best Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.303", "pdf_url": "", "track": null,...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Best
Title: REL-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance Abstract: The ability to communicate uncertainty and knowledge limitations is crucial for the safety of large language models (LLMs). Current evaluations of these abilities typically examine the correspondence between model accuracy and it...
{ "conference": "NAACL 2025", "category": "Best Paper Runner-up", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.556", "pdf_url": "", "trac...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Best
Title: FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation Abstract: Sign language translation has historically been peripheral to mainstream machine translation research. In order to help converge the fields, we introduce FLEURS-ASL, an extension of the multiway parallel benchma...
{ "conference": "NAACL 2025", "category": "Best Social Impact Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.314", "pdf_url": "", ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Best
Title: WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines Abstract: Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts. To evaluate thei...
{ "conference": "NAACL 2025", "category": "Best Theme Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.167", "pdf_url": "", "track":...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Best
Title: Developing multilingual speech synthesis system for Ojibwe, Mi’kmaq, and Maliseet Abstract: We present lightweight flow matching multilingual text-to-speech (TTS) systems for Ojibwe, Mi’kmaq, and Maliseet, three Indigenous languages in North America. Our results show that training a multilingual TTS model on t...
{ "conference": "NAACL 2025", "category": "Best Theme Paper Runner-up", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-short.69", "pdf_url": "", ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: PeerQA: A Scientific Question Answering Dataset from Peer Reviews Abstract: We present PeerQA, a real-world, scientific, document-level Question Answering (QA) dataset. PeerQA questions have been sourced from peer reviews, which contain questions that reviewers raised while thoroughly examining the scientific ar...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.22", "pdf_url": "", "track": ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Is your benchmark truly adversarial? AdvScore: Evaluating Human-Grounded Adversarialness Abstract: Adversarial datasets should validate AI robustness by providing samples on which humans perform well, but models do not. However, as models evolve, datasets can become obsolete. Measuring whether a dataset remains ...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.27", "pdf_url": "", "track": ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: NLI under the Microscope: What Atomic Hypothesis Decomposition Reveals Abstract: Decomposition of text into atomic propositions is a flexible framework allowing for the closer inspection of input and output text. We use atomic decomposition of hypotheses in two natural language reasoning tasks, traditional NLI a...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.130", "pdf_url": "", "track"...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models Abstract: Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource languages (e.g. African languages) are of...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.139", "pdf_url": "", "track":...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: ACCORD: Closing the Commonsense Measurability Gap Abstract: We present ACCORD, a framework and benchmark suite for disentangling the commonsense grounding and reasoning abilities of large language models (LLMs) through controlled, multi-hop counterfactuals. ACCORD introduces formal elements to commonsense reason...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.193", "pdf_url": "", "track"...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students’ Hand-Drawn Math Images Abstract: In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digit...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.352", "pdf_url": "", "track"...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: A Logical Fallacy-Informed Framework for Argument Generation Abstract: Despite the remarkable performance of large language models (LLMs), they still struggle with generating logically sound arguments, resulting in potential risks such as spreading misinformation. An important factor contributing to LLMs’ subo...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.374", "pdf_url": "", "track"...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Learning vs Retrieval: The Role of In-Context Examples in Regression with Large Language Models Abstract: Generative Large Language Models (LLMs) are capable of being in-context learners. However, the underlying mechanism of in-context learning (ICL) is still a major research question, and experimental research ...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.417", "pdf_url": "", "track":...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: Multi3Hate: Multimodal, Multilingual, and Multicultural Hate Speech Detection with Vision–Language Models Abstract: Hate speech moderation on global platforms poses unique challenges due to the multimodal and multilingual nature of content, along with the varying cultural perceptions. How well do current vision-...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.490", "pdf_url": "", "track"...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Outstanding
Title: How Good Are LLMs for Literary Translation, Really? Literary Translation Evaluation with Humans and LLMs Abstract: Recent research has focused on literary machine translation (MT) as a new challenge in MT. However, the evaluation of literary MT remains an open problem. We contribute to this ongoing discussion by...
{ "conference": "NAACL 2025", "category": "Outstanding Paper", "sheet": "NAACL", "accepted_tags": "NAACL 2025", "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.548", "pdf_url": "", "track"...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: MEXA: Multilingual Evaluation of English-Centric LLMs via Cross-Lingual Alignment Abstract: English-centric large language models (LLMs) often show strong multilingual capabilities. However, their multilingual performance remains unclear and is under-evaluated for many other languages. Most benchmarks for multil...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.1385", "pdf_url": "", "track": "findings", "confere...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Towards Explainable Hate Speech Detection Abstract: Recent advancements in deep learning have significantly enhanced the efficiency and accuracy of natural language processing (NLP) tasks. However, these models often require substantial computational resources, which remains a major drawback. Reducing the comple...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.667", "pdf_url": "", "track": "findings", "confere...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Disambiguate First, Parse Later: Generating Interpretations for Ambiguity Resolution in Semantic Parsing Abstract: Handling ambiguity and underspecification is an important challenge in natural language interfaces, particularly for tasks like text-to-SQL semantic parsing. We propose a modular approach that resol...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.863", "pdf_url": "", "track": "findings", "conferen...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: EssayJudge: A Multi-Granular Benchmark for Assessing Automated Essay Scoring Capabilities of Multimodal Large Language Models Abstract: Automated Essay Scoring (AES) plays a crucial role in educational assessment by providing scalable and consistent evaluations of writing tasks. However, traditional AES systems ...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.329", "pdf_url": "", "track": "findings", "conferen...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Unsupervised Morphological Tree Tokenizer Abstract: As a cornerstone in language modeling, tokenization involves segmenting text inputs into pre-defined atomic units. Conventional statistical tokenizers often disrupt constituent boundaries within words, thereby corrupting semantic information. To address this dr...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.1146", "pdf_url": "", "track": "findings", "confere...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: ^2 M-TabFact: Multi-Document Multi-Modal Fact Verification with Visual and Textual Representations of Tabular Data Abstract: Tabular data is used to store information in many real-world systems ranging from finance to healthcare. However, such structured data is often communicated to humans in visually interpret...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.1345", "pdf_url": "", "track": "findings", "confer...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Federated Data-Efficient Instruction Tuning for Large Language Models Abstract: Instruction tuning is a crucial step in improving the responsiveness of pretrained large language models (LLMs) to human instructions. Federated learning (FL) helps to exploit the use of vast private instruction data from clients, be...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.803", "pdf_url": "", "track": "findings", "conferen...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Generative Error Correction for Emotion-aware Speech-to-text Translation Abstract: This paper explores emotion-aware speech-to-text translation (ST) using generative error correction (GER) by large language models (LLMs). Despite recent advancements in ST, the impact of the emotional content has been overlooked....
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.1047", "pdf_url": "", "track": "findings", "confere...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: MotiveBench: How Far Are We From Human-Like Motivational Reasoning in Large Language Models? Abstract: Large language models (LLMs) have been widely adopted as the core of agent frameworks in various scenarios, such as social simulations and AI companions. However, the extent to which they can replicate human-li...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.1029", "pdf_url": "", "track": "findings", "confere...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data Abstract: In real-world NLP applications, Large Language Models (LLMs) offer promising solutions due to their extensive training on vast datasets. However, the large size and high computation demands of LLMs limit their prac...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.142", "pdf_url": "", "track": "findings", "confer...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language Models Abstract: The rapid evolution of large language models (LLMs) has transformed the competitive landscape in natural language processing (NLP), particularly for English and other data-rich languages. However, underrepre...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.253", "pdf_url": "", "track": "findings", "confer...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators Abstract: Triton, a high-level Python-like language designed for building efficient GPU kernels, is widely adopted in deep learning frameworks due to its portability, flexibility, and accessibility. However, programming a...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.1183", "pdf_url": "", "track": "findings", "confere...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: ProMind-LLM: Proactive Mental Health Care via Causal Reasoning with Sensor Data Abstract: Mental health risk is a critical global public health challenge, necessitating innovative and reliable assessment methods. With the development of large language models (LLMs), they stand out to be a promising tool for expl...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.1033", "pdf_url": "", "track": "findings", "confere...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: ClaimPKG: Enhancing Claim Verification via Pseudo-Subgraph Generation with Lightweight Specialized LLM Abstract: Integrating knowledge graphs (KGs) to enhance the reasoning capabilities of large language models (LLMs) is an emerging research challenge in claim verification. While KGs provide structured, semantic...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-acl.274", "pdf_url": "", "track": "findings", "conferen...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: Diffusion Models Through a Global Lens: Are They Culturally Inclusive? Abstract: Text-to-image diffusion models have recently enabled the creation of visually compelling, detailed images from textual prompts. However, their ability to accurately represent various cultural nuances remains an open question. In our...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1503", "pdf_url": "", "track": "main", "conference_group":...
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[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory Abstract: The proliferation of web agents necessitates advanced navigation and interaction strategies within complex web environments. Current models often struggle with efficient navigation and action execution due to limi...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.1464", "pdf_url": "", "track": "main", "conference_group": ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: BELLE: A Bi-Level Multi-Agent Reasoning Framework for Multi-Hop Question Answering Abstract: Multi-hop question answering (QA) involves finding multiple relevant passages and performing step-by-step reasoning to answer complex questions. Previous works on multi-hop QA employ specific methods from different model...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.211", "pdf_url": "", "track": "main", "conference_group": "...
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[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: LLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs Abstract: Detecting tricky bugs in plausible programs, those that pass existing test suites yet still contain bugs, remains a significant challenge in software testing. To address this problem, we propose TrickCatcher, an LLM-powered appro...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.20", "pdf_url": "", "track": "main", "conference_group": "a...
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[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: AdaDHP: Fine-Grained Fine-Tuning via Dual Hadamard Product and Adaptive Parameter Selection Abstract: With the continuously expanding parameters, efficiently adapting large language models to downstream tasks is crucial in resource-limited conditions. Many parameter-efficient fine-tuning methods have emerged to ...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.467", "pdf_url": "", "track": "main", "conference_group": "...
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[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: My Words Imply Your Opinion: Reader Agent-Based Propagation Enhancement for Personalized Implicit Emotion Analysis Abstract: The subtlety of emotional expressions makes implicit emotion analysis (IEA) particularly sensitive to user-specific characteristics. Current studies personalize emotion analysis by focusin...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.787", "pdf_url": "", "track": "main", "conference_group": ...
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[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: Explicit and Implicit Data Augmentation for Social Event Detection Abstract: Social event detection involves identifying and categorizing important events from social media, which relies on labeled data, but annotation is costly and labor-intensive. To address this problem, we propose Augmentation framework for ...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.412", "pdf_url": "", "track": "main", "conference_group": "...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: A Variational Approach for Mitigating Entity Bias in Relation Extraction Abstract: Mitigating entity bias is a critical challenge in Relation Extraction (RE), where models often rely excessively on entities, resulting in poor generalization. This paper presents a novel approach to address this issue by adapting ...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-short.53", "pdf_url": "", "track": "main", "conference_group": "...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric Abstract: Data diversity is crucial for the instruction tuning of large language models. Existing studies have explored various diversity-aware data selection methods to construct high-quality datasets and enhance model ...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.908", "pdf_url": "", "track": "main", "conference_group": "...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: Generative Psycho-Lexical Approach for Constructing Value Systems in Large Language Models Abstract: Values are core drivers of individual and collective perception, cognition, and behavior. Value systems, such as Schwartz’s Theory of Basic Human Values, delineate the hierarchy and interplay among these values, ...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.585", "pdf_url": "", "track": "main", "conference_group": ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: DioR: Adaptive Cognitive Detection and Contextual Retrieval Optimization for Dynamic Retrieval-Augmented Generation Abstract: Dynamic Retrieval-augmented Generation (RAG) has shown great success in mitigating hallucinations in large language models (LLMs) during generation. However, existing dynamic RAG methods ...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.148", "pdf_url": "", "track": "main", "conference_group": ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: TWIST: Text-encoder Weight-editing for Inserting Secret Trojans in Text-to-Image Models Abstract: Text-to-image (T2I) models excel at generating high-quality images from text via powerful text encoders but training these encoders demands substantial computational resources. Consequently, many users seek pre-trai...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.541", "pdf_url": "", "track": "main", "conference_group": ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench Abstract: The advent of Large Language Models (LLMs) has spurred the development of coding agents for real-world code generation.As a widely used benchmark for evaluating the code generation capabilities of these agents, SWE-Bench uses real-world problem...
{ "conference": "ACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "acl2025_main.csv", "url": "https://aclanthology.org/2025.acl-long.189", "pdf_url": "", "track": "main", "conference_group": ...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: LVLM-Compress-Bench: Benchmarking the Broader Impact of Large Vision-Language Model Compression Abstract: Despite recent efforts in understanding the compression impact on Large Language Models (LLMs) in terms of their downstream task performance and trustworthiness on relatively simpler uni-modal benchmarks (e....
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.84", "pdf_url": "", "track": "findings", "con...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Analysis of LLM as a grammatical feature tagger for African American English Abstract: African American English (AAE) presents unique challenges in natural language processing (NLP) This research systematically compares the performance of available NLP models—rule-based, transformer-based, and large language mod...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.431", "pdf_url": "", "track": "findings", "co...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: GRAG: Graph Retrieval-Augmented Generation Abstract: Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in many applications such as citation graphs, social media, and knowledge graphs. T...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.232", "pdf_url": "", "track": "findings", "c...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Multi-Condition Guided Diffusion Network for Multimodal Emotion Recognition in Conversation Abstract: Emotion recognition in conversation (ERC) involves identifying emotional labels associated with utterances within a conversation, a task that is essential for developing empathetic robots. Current research empha...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.177", "pdf_url": "", "track": "findings", "co...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Task-wrapped Continual Learning in Task-Oriented Dialogue Systems Abstract: Continual learning is vital for task-oriented dialogue systems (ToDs), and AdapterCL, equipped with residual adapters, has proven effectiveness in this domain. However, its performance is limited by training separate adapters for each ta...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.174", "pdf_url": "", "track": "findings", "co...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Understanding the Role of Mental Models in User Interaction with an Adaptive Dialog Agent Abstract: Mental models play an important role in whether user interactions with intelligent systems, such as dialog agents, are successful. Adaptive dialog systems present the opportunity to align a dialog agent’s behavior...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.56", "pdf_url": "", "track": "findings", "con...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: SimSMoE: Toward Efficient Training Mixture of Experts via Solving Representational Collapse Abstract: Sparse mixture of experts (SMoE) have emerged as an effective approach for scaling large language models while keeping a constant computational cost. Regardless of several notable successes of SMoE, effective tr...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.107", "pdf_url": "", "track": "findings", "c...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Uncovering Latent Arguments in Social Media Messaging by Employing LLMs-in-the-Loop Strategy Abstract: The widespread use of social media has led to a surge in popularity for automated methods of analyzing public opinion. Supervised methods are adept at text categorization, yet the dynamic nature of social media...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.413", "pdf_url": "", "track": "findings", "c...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Lost in the Distance: Large Language Models Struggle to Capture Long-Distance Relational Knowledge Abstract: Large language models (LLMs) have demonstrated impressive capabilities in handling long contexts, but challenges remain in capturing relational knowledge spread far apart within text. Connecting long-dist...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.256", "pdf_url": "", "track": "findings", "c...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization Abstract: Most research on abstractive summarization focuses on single-domain applications, often neglecting how domain shifts between documents affect performance and the generalization ability of summarization m...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.118", "pdf_url": "", "track": "findings", "c...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: MoLA: MoE LoRA with Layer-wise Expert Allocation Abstract: Recent efforts to integrate low-rank adaptation (LoRA) with the Mixture-of-Experts (MoE) have managed to achieve performance comparable to full-parameter fine-tuning by tuning much fewer parameters. Despite promising results, research on improving the ef...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.284", "pdf_url": "", "track": "findings", "co...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: 2D-DPO: Scaling Direct Preference Optimization with 2-Dimensional Supervision Abstract: Recent advancements in Direct Preference Optimization (DPO) have significantly enhanced the alignment of Large Language Models (LLMs) with human preferences, owing to its simplicity and effectiveness. However, existing method...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.455", "pdf_url": "", "track": "findings", "co...
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[ "Findings", "Main", "Outstanding", "Best" ]
Findings
Title: Rationale Behind Essay Scores: Enhancing S-LLM’s Multi-Trait Essay Scoring with Rationale Generated by LLMs Abstract: Existing automated essay scoring (AES) has solely relied on essay text without using explanatory rationales for the scores, thereby forgoing an opportunity to capture the specific aspects evaluat...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_findings.csv", "url": "https://aclanthology.org/2025.findings-naacl.322", "pdf_url": "", "track": "findings", "c...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: Towards Lifelong Dialogue Agents via Timeline-based Memory Management Abstract: To achieve lifelong human-agent interaction, dialogue agents need to constantly memorize perceived information and properly retrieve it for response generation (RG). While prior studies focus on getting rid of outdated memories to im...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.435", "pdf_url": "", "track": "main", "conference_gr...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: Beyond Benchmarks: Building a Richer Cross-Document Event Coreference Dataset with Decontextualization Abstract: Cross-Document Event Coreference (CDEC) annotation is challenging and difficult to scale, resulting in existing datasets being small and lacking diversity. We introduce a new approach leveraging large...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.178", "pdf_url": "", "track": "main", "conference_gr...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection Abstract: Recent advances on instruction fine-tuning have led to the development of various prompting techniques for large language models, such as explicit reasoning steps. However, the success of techniques depends on various parameters, s...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.122", "pdf_url": "", "track": "main", "conference_gro...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity Abstract: Researchers in social science and psychology have recently proposed using large language models (LLMs) as replacements for humans in behavioral research. In addition to arguments about whether LLMs accura...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.561", "pdf_url": "", "track": "main", "conference_gro...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: On the Analysis and Distillation of Emergent Outlier Properties in Pre-trained Language Models Abstract: A small subset of dimensions within language Transformers’ representation spaces emerge as “outliers” during pretraining, encoding critical knowledge sparsely. We extend previous findings on emergent ou...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.430", "pdf_url": "", "track": "main", "conference_gr...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy Abstract: There is a significant gap between patient needs and available mental health support today. In this paper, we aim to thoroughly examine the potential of using Large Language Models (LLMs) to assist professional psychoth...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": false, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.196", "pdf_url": "", "track": "main", "conference_gr...
Which recognition tier (Findings/Main/Outstanding/Best) best fits this paper?
[ "Findings", "Main", "Outstanding", "Best" ]
Main
Title: A Novel Computational Modeling Foundation for Automatic Coherence Assessment Abstract: Coherence is an essential property of well-written texts, that refers to the way textual units relate to one another. In the era of generative AI, coherence assessment is essential for many NLP tasks such as summarization, lon...
{ "conference": "NAACL 2025", "category": null, "sheet": null, "accepted_tags": null, "authors_included": true, "year": 2025, "cutoff_period": "future_2025", "source_csv": "naacl2025_main.csv", "url": "https://aclanthology.org/2025.naacl-long.277", "pdf_url": "", "track": "main", "conference_gro...
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