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Computation & Language / NLP
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Newest papers, page 36
Learning Scientific Trajectories to Predict Future Biomedical Discoveries
AI co-scientists have expanded the use of large language models for generating scientific hypotheses and guiding experimental investigation.The Quine Test: How Much of a Model's Self Survives Its Own Description?
Frontier language models express coherent preferences, but behavioral evidence alone cannot say whether these belong to the model or to a character it portrays.AtomTree: A Hierarchical Framework for State-Aware Embodied Instruction Following with LLMs
Embodied instruction following in interactive environments requires agents to interpret natural language commands and complete long-horizon tasks.Gold vs.~Translation: Are We Measuring Language, Knowledge, or Locality in Translated Benchmarks?
Translated versions of English-origin benchmarks such as MMLU are widely used to evaluate large language models in non-English languages, yet it remains unclear whether they measure the same…CopyLoop: Fast Looped Transformer Decoding via Context Copying and Shallow Screening
Looped Transformers increase computational capacity through the repeated application of shared blocks, but their recurrent depth makes conventional full-depth decoding expensive.What to randomize matters: a controlled study of volume, axis and representation in low-data molecular generation
Chemical language models can struggle to generate new molecules when trained on small datasets, where a model may reproduce training examples rather than learn a useful generative distribution.Contextual Embeddings Beyond the Gold Chunk
Contextual embeddings represent chunks of a document with respect to the document's global context.HEDGE: Gated Hypergraph Memory for Scalable Multi-Agent Debate
Multi-agent debate systems require agents to retain and revisit arguments across multiple rounds, yet limited context windows and unstructured memories make relevant information increasingly…Interventional Training Reduces Causal Bypass in In-Context Introspection
Introspection, the ability of a system to access and reason about its internal signals, is crucial for language model (LM) self-consistency and scalable interpretability.Efficient Agentic Audio-Visual Question Answering through Toolset Pruning and Modality Consolidation
Fine-grained audio-visual question answering (AVQA) requires models to resolve complex cross-modal correspondences and temporally grounding from sparsely distributed evidence.Beyond Passing Tests: A Systematic Review and Controlled Re-evaluation of Techniques for Improving the Quality of LLM-Generated Code
Large language models pass most functional-correctness benchmarks, but passing tests says little about whether their code is readable, efficient or secure.How Architecture, Typology, and Adaptation Strategies Shape ASR for Low-Resource African Languages: A Controlled Empirical Study
Despite recent advancements in ASR, identifying effective architectures, fine-tuning approaches, and data adaptation strategies for low-resource languages remains challenging.Blind Spots: Where Small Language Models Fall Behind Frontier Models on Terminal Tasks
Small language models (SLMs) offer an attractive alternative to frontier models (FMs) because they can be deployed with lower cost and latency.Implicit Reasoning in Transformers: Bridging the Compositionality Gap in GPT-2-like Models
Compositional generalization remains a persistent limitation of transformer language models: even when a model learns to combine known facts correctly in-distribution (ID), the same compositional…Author-Informed Stance Detection: A Dataset and Findings
Stance detection in social media is challenging, as interpreting a text often requires understanding the author's perspective.Distilling the Shape of Uncertainty: What On-Policy Distillation Learns and How to Predict It
On-policy distillation (OPD) is increasingly adopted in the post-training of large language models.Tracing the Influence of Retrieved Literature on Scientific Ideation in LLMs
Large language models (LLMs) are increasingly used to generate research ideas from scientific literature.HEARSAYBENCH: Can AI Navigate from Abstract Human Rights to Lived Lives?
As large language models (LLMs) reach users worldwide, personal counseling has emerged as one of their most consequential applications, sometimes in life-critical situations.No Tokenizer, Still a Gap: Cross-Lingual Fairness of Homoglyph and Invisible-Character Watermarking
Homoglyph and invisible-character watermarks are edit-based watermarks.CONCUR: Concordant Auxiliary Rewards for Multi-Task, Multi-Reward Reinforcement Learning
When a Large Language Model (LLM) is trained with Reinforcement Learning (RL) on multiple tasks, a task's primary reward can gate auxiliary rewards such as a length reward: on a failing response, an…