2 citations · 8 across the 46 of their papers we have counts for
23 papers · 1 filter
CrossWeave: Bridging Perspectives Across Online Communities with a Dual-Pane Design
Fei Fang, Reva Hirave, William Jurayj +19
Social media systems typically display conversations among already familiar contributors, which can be predictable and one-sided. In civic discourse, this design narrows discussion…
SIGMA: Self-Improving Alignment Generalization from a Model Spec
Jingyu Zhang, Shruti Palaskar, Daniel Khashabi +3
LLM agents are increasingly capable of executing complex tasks and of recursively improving themselves on easy-to-verify objectives such as software engineering and mathematics. Si…
JEPA-TTT: Persistent Test-Time Training of Latent World Models for Planning under Dynamics Shifts
Zheyuan Zhang, Suyu Ye, Nakul Agarwal +5
World models enable agents to plan by predicting future states of the environment, but their predictions can become unreliable when test-time dynamics differ from those seen during…
Harness Learning Enables Generalizable Test-Time Adaptation
Alvin Zhang, Xuecheng Liu, Zixuan Wang +6
A language-model agent is jointly defined by its model and its harness, the executable program that organizes model calls, tool use, and information flow. Because different tasks c…
Minimally Invasive Steering of Language Models
Taha Entesari, Jingyu Zhang, Daniel Khashabi +1
Pre-logit steering adapts a frozen language model to a test-time reward by adding vectors to its final hidden states. Unregularized reward optimization can substantially alter the…
Convergent Emergence of In-Context Learning Across Modalities
Nathan Breslow, Seungwook Han, Daniel Hyunsoo Lee +3
Few-shot in-context learning (ICL), the capacity of a model to infer abstract patterns from input-output examples provided in its prompt and apply them to new inputs, has been exte…
Continual Learning Mechanisms Compose for Long-Horizon Memorization
Zheyuan Zhang, Alvin Zhang, Daniel Khashabi +1
Language models may need to internalize information that arrives over time and retain it through many subsequent updates. To study this challenge, we introduce long-horizon memoriz…
VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning
Junxiang Xu, Ruisi Wang, Fanyi Pu +49
Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be understood or outputs to be r…
Information Abundance Paradox: Long-Context Training Undermines Parametric Knowledge
Arda Uzunoglu, Benjamin Van Durme, Daniel Khashabi
Large language models are increasingly trained and deployed with long contexts that span documents, code repositories, and interaction histories. This scaling reflects the implicit…
Better, Faster, Stronger: Programmatic Skill Learning Best Reduces Agent Cost
Zixi Huang, Xiheng Wang, Andrew Wang +4
Recently, the practice of augmenting LLM agent capability with skills has gained prevalence. We explore the cost effective adaptation of agents to novel domains by means of learnin…
Self-Compacting Language Model Agents
Tianjian Li, Jingyu Zhang, William Jurayj +5
Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context window. Existing scaf…
Trust Functions: Near-Lossless Weak-to-Strong Generalization by Learning When to Trust the Weak Teacher
Arda Uzunoglu, Alvin Zhang, Daniel Khashabi
Weak-to-strong generalization studies how to improve a strong student using supervision from a weaker teacher when reliable labels are scarce. We view this primarily as a data sele…
AgentOdyssey: Open-Ended Long-Horizon Text Game Generation for Test-Time Continual Learning Agents
Zheyuan Zhang, Zehao Wen, Alvin Zhang +4
For agents to learn continuously from interaction with the world at test time, they must be able to explore effectively, acquire new world knowledge and skills, retain relevant epi…
Steered LLM Activations are Non-Surjective
Aayush Mishra, Daniel Khashabi, Anqi Liu
Activation steering is a popular white-box control technique that modifies model activations to elicit an abstract change in its behavior. It has also become a standard tool in int…
Can Coding Agents Reproduce Findings in Computational Materials Science?
Ziyang Huang, Yi Cao, Ali K. Shargh +15
Large language models are increasingly deployed as autonomous coding agents and have achieved remarkably strong performance on software engineering benchmarks. However, it is uncle…
GENFIG1: Visual Summaries of Scholarly Work as a Challenge for Vision-Language Models
Yaohan Guan, Pristina Wang, Najim Dehak +3
In many science papers, "Figure 1" serves as the primary visual summary of the core research idea. These figures are visually simple yet conceptually rich, often requiring signific…
Are Finer Citations Always Better? Rethinking Granularity for Attributed Generation
Hexuan Wang, Jingyu Zhang, Benjamin Van Durme +1
Citation granularity -- whether to cite individual sentences, paragraphs, or documents -- is a critical design choice in attributed generation. While fine-grained citations are com…
Many-Tier Instruction Hierarchy in LLM Agents
Jingyu Zhang, Tianjian Li, William Jurayj +3
Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, other agents, and more-each carrying different levels of trust and a…
Crystal: Characterizing Relative Impact of Scholarly Publications
Hannah Collison, Benjamin Van Durme, Daniel Khashabi
Assessing a cited paper's impact is typically done by analyzing its citation context in isolation within the citing paper. While this focuses on the most directly relevant text, it…
Safe and Interpretable Multimodal Path Planning for Multi-Agent Cooperation
Haojun Shi, Suyu Ye, Katherine M. Guerrerio +5
Successful cooperation among decentralized agents requires each agent to quickly adapt its plan to the behavior of other agents. In scenarios where agents cannot confidently predic…
A Very Big Video Reasoning Suite
Maijunxian Wang, Ruisi Wang, Juyi Lin +53
Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grounds intelligence in spatiotemporally c…
Conformal Thinking: Risk Control for Reasoning on a Compute Budget
Xi Wang, Anushri Suresh, Alvin Zhang +6
Reasoning Large Language Models (LLMs) enable test-time scaling, with dataset-level accuracy improving as the token budget increases, motivating adaptive reasoning -- spending toke…
More Than Efficiency: Embedding Compression Improves Domain Adaptation in Dense Retrieval
Chunsheng Zuo, Daniel Khashabi
Dense retrievers powered by pretrained embeddings are widely used for document retrieval but struggle in specialized domains due to the mismatches between the training and target d…